Excitatory cholecystokinin neurons of the midbrain integrate diverse temporal responses and drive auditory thalamic subdomains.

The central nucleus of the inferior colliculus (ICC) integrates information about different features of sound and then distributes this information to thalamocortical circuits. However, the lack of clear definitions of circuit elements in the ICC has limited our understanding of the nature of these circuit transformations. Here, we combine virus-based genetic access with electrophysiological and optogenetic approaches to identify a large family of excitatory, cholecystokinin-expressing thalamic projection neurons in the ICC of the Mongolian gerbil. We show that these neurons form a distinct cell type, displaying uniform morphology and intrinsic firing features, and provide powerful, spatially restricted excitation exclusively to the ventral auditory thalamus. In vivo, these neurons consistently exhibit V-shaped receptive field properties but strikingly diverse temporal responses to sound. Our results indicate that temporal response diversity is maintained within this population of otherwise uniform cells in the ICC and then relayed to cortex through spatially restricted thalamic subdomains.

An Anatomical and Physiological Basis for Flexible Coincidence Detection in the Auditory System.

Animals navigate the auditory world by recognizing complex sounds, from the rustle of a predator to the call of a potential mate. This ability depends in part on the octopus cells of the auditory brainstem, which respond to multiple frequencies that change over time, as occurs in natural stimuli. Unlike the average neuron, which integrates inputs over time on the order of tens of milliseconds, octopus cells must detect momentary coincidence of excitatory inputs from the cochlea during an ongoing sound on both the millisecond and submillisecond time scale. Here, we show that octopus cells receive inhibitory inputs on their dendrites that enhance opportunities for coincidence detection in the cell body, thereby allowing for responses both to rapid onsets at the beginning of a sound and to frequency modulations during the sound. This mechanism is crucial for the fundamental process of integrating the synchronized frequencies of natural auditory signals over time.

Intrinsic firing properties in the avian auditory brain stem allow both integration and encoding of temporally modulated noisy inputs in vitro.

The intrinsic properties of tonically firing neurons in the cochlear nucleus contribute to representing average sound intensity by favoring synaptic integration across auditory nerve inputs, reducing phase locking to fine temporal acoustic structure and enhancing envelope locking. To determine whether tonically firing neurons of the avian cochlear nucleus angularis (NA) resemble ideal integrators, we investigated their firing responses to noisy current injections during whole cell patch-clamp recordings in brain slices. One subclass of neurons (36% of tonically firing neurons, mainly subtype tonic III) showed no significant changes in firing rate with noise fluctuations, acting like pure integrators. In contrast, many tonically firing neurons (>60%, mainly subtype tonic I or II) showed a robust sensitivity to noisy current fluctuations, increasing their firing rates with increased fluctuation amplitudes. For noise-sensitive tonic neurons, the firing rate vs. average current curves with noise had larger maximal firing rates, lower gains, and wider dynamic ranges compared with FI curves for current steps without noise. All NA neurons showed fluctuation-driven patterning of spikes with a high degree of temporal reliability and millisecond spike time precision. Single-spiking neurons in NA also responded to noisy currents with higher firing rates and reliable spike trains, although less precisely than nucleus magnocellularis neurons. Thus some NA neurons function as integrators by encoding average input levels over wide dynamic ranges regardless of current fluctuations, others detect the degree of coherence in the inputs, and most encode the temporal patterns contained in their inputs with a high degree of precision.

Dissecting the Roles of GABA and Neuropeptides from Rat Central Amygdala CRF Neurons in Anxiety and Fear Learning.

Central amygdala (CeA) neurons that produce corticotropin-releasing factor (CRF) regulate anxiety and fear learning. These CeACRF neurons release GABA and several neuropeptides predicted to play important yet opposing roles in these behaviors. We dissected the relative roles of GABA, CRF, dynorphin, and neurotensin in CeACRF neurons in anxiety and fear learning by disrupting their expression using RNAi in male rats. GABA, but not CRF, dynorphin, or neurotensin, regulates baseline anxiety-like behavior. In contrast, chemogenetic stimulation of CeACRF neurons evokes anxiety-like behavior dependent on CRF and dynorphin, but not neurotensin. Finally, knockdown of CRF and dynorphin impairs fear learning, whereas knockdown of neurotensin enhances it. Our results demonstrate distinct behavioral roles for GABA, CRF, dynorphin, and neurotensin in a subpopulation of CeA neurons. These results highlight the importance of considering the repertoire of signaling molecules released from a given neuronal population when studying the circuit basis of behavior.

Functional Access to Neuron Subclasses in Rodent and Primate Forebrain.

Viral vectors enable foreign proteins to be expressed in brains of non-genetic species, including non-human primates. However, viruses targeting specific neuron classes have proved elusive. Here we describe viral promoters and strategies for accessing GABAergic interneurons and their molecularly defined subsets in the rodent and primate. Using a set intersection approach, which relies on two co-active promoters, we can restrict heterologous protein expression to cortical and hippocampal somatostatin-positive and parvalbumin-positive interneurons. With an orthogonal set difference method, we can enrich for subclasses of neuropeptide-Y-positive GABAergic interneurons by effectively subtracting the expression pattern of one promoter from that of another. These methods harness the complexity of gene expression patterns in the brain and significantly expand the number of genetically tractable neuron classes across mammals.